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scaled vs canonical #14
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Personally I find "scaled" much more clear than "canonical", though I understand the interest in being consistent. |
Also "scaled" is more consistent with how we name the other matrices as "unconstrained" and "rank-1", which alludes to how these matrices are parameterized. |
I do agree that "scaled" is more consistent with "unconstrained". If we are estimating U_k = sU_0 then I would say that U_0 is the "canonical" matrix and |
maybe we can keep scaled here and make the connection with canonical matrices in the documentation.... |
Maybe we keep "scaled.update" for now and make a connection between "scaled" and canonical covariance matrices in the documents? And I agree that U0 is a canonical matrix and U (=s*U0) is a scaled matrix. Scaled/unconstrained/rank1 updates are consistent. |
I wonder if maybe we should refer to the "scaled" matrices as "canonical" to be consistent with mashr
(and mvsusieR). Or at least use canonical to refer to the matrices that are being scaled.
eg in
ud_init
theU_scaled
parameter would becomeU_canonical
?(Is it too confusing to use scaled.update to refer to the updates that estimate the scaling of the canonical matrices?)
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